Why Logistics Data Matter...

Why Logistics Data Matters in Retail

Oct 03, 2023
Why Logistics Data Matters in Retail

Modern omnichannel retailing is all about data.

Data can change all aspects of a retailer, from tailoring the offer to each and every customer in all channels to allowing supply chains to become more dynamic. Each retailer needs to increasingly master personalization in the front-end and full flexibility and dynamism in the back-end if they want to become true omnichannel retailers. According to Karl Prag, Chief Digital Officer at CEVA Logistics, “the ability to connect data all the way from suppliers to customers is essential as this makes it possible to fulfill the requirements of true omnichannel retailing, meeting the customers where they are and in the way(s) they want.”

Having said that, what exactly is logistics data? What are some real-life applications of this “data” that we speak of? Let’s find out!

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What Is Logistics Data?

Why Logistics Data Matter in Retail KPIs

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Logistics data serves as a reliable source of information for companies to evaluate Key Performance Indicators (KPIs). Businesses utilize this data to optimize their operations, gain knowledge about industry trends and make decisions about technological investments. Data that is accurate, clean and structured will give companies the insights they need to make more informed decisions. Building analytics on flawed data, on the other hand, exposes even the most sophisticated infrastructure to a compromise.

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Benefits of Logistics Data in Retail and E-Commerce

Big data is helping retailers and e-commerce stores worldwide to better understand consumer habits and streamline operations.

Retail giant Walmart, for instance, is developing the ‘world’s largest private cloud’, with algorithms built to track data on inventory, transactions and competitor activity. This will allow the company to respond to market changes almost instantly. Another excellent example is Amazon, with 35% of its revenues generated by its customer recommendations algorithm, which is based on data collection and big data marketing and sales strategies.

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Indeed, there is no end to what you can accomplish by effectively using logistics data. If you are still not convinced by the aforementioned real life examples, continue reading to learn more about the benefits of logistics data.

#1: Predict Upcoming E-Commerce and Retail Trends to Stay Ahead of the Competition

Businesses can use logistics data to assign value to things in stock, whether they are best-seller items or those that don't produce sales. Utilizing this information helps retail and e-commerce companies to build marketing efforts around major events, as well as anticipate new e-commerce trends.

There is no shortage of datasets for most e-commerce firms. By analyzing data from prior years, these e-tailers can plan inventory accordingly, stock up to arrange inventory accordingly, streamline overall business operations, and forecast demand. For example, to get rid of extra merchandise, e-commerce businesses can advertise large markdowns on social media during peak shopping times to get rid of excess products. Besides, if any items are no longer in peak demand, companies can consider importing less of them. Such products not only take up space in a warehouse but also waste the time of the company staff who still have to account for them in the inventory.

#2: Understand Customers to Maximize Sales 

E-commerce stores can find previously unidentified customer wants with the help of in-depth data analytics. After collecting data from a variety of consumer engagement channels, including websites, social media, internet searches, online questionnaires, email marketing, marketers and e-store owners will have overview information of their online shoppers as well as gain more insights into their interactions and preferences. Such valuable information will show client purchasing habits, top brands, most-searched products, and shopping trends, allowing e-commerce businesses to see recurrent patterns and alter their offerings accordingly.

By extracting the right details from the right channels, retailers can find precise answers to the following questions:

  • How do your customers better engage with your store?

  • What are their favorite products?

  • What similar items are individuals also looking at (as a potential upsell or cross-sell opportunity)?

  • How is their paying experience? 

  • What about their post-purchase experience? How many of them are returning their purchased goods?

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#3: Improve Customer Experience to Earn Loyal Customers

Customer experience is undeniably one of the most important criteria in determining a logistics company's success. Businesses that meet or, better still, exceed customer expectations have higher retention and conversion rates, as well as larger profit margins. So, how exactly can a company understand and meet the requirements of its customers? With the support of logistics data in retail and e-commerce, you can achieve that aim.

For instance, retailers can determine the most effective communication routes for contacting their shoppers and predict when they are ready to make purchases, etc. Furthermore, evaluating those logistics data can assist such businesses in competently and automatically capturing client wants, feedback, and expectations, allowing them to adapt their processes and minimize inefficiencies. By doing that, logistics companies can consequently boost the overall customers' experience.

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#4: Boost Efficiency to Increase Bottom Line 

Another advantage of effective data usage is boosting operational efficiency. Data plays a crucial role in achieving uptime. To be more specific, using big data as a data-driven lifecycle management system can help link people and technology, hence controlling and maintaining the equipment better. If logistics companies can utilize big data in operating their system, they can maximize the uptime and minimize disruptions. This way, they can achieve higher productivity as compared to the traditional management system.

Using big data to manage and maintain the equipment can help increase efficiency and reduce disruptions. To further optimize this process, organizations can use tools like SQL index performance analyzer to help identify and analyze SQL index performance issues to ensure optimal database performance. This way, organizations can reduce system failures, downtime, and other issues, leading to a higher bottom line in the long run.

Using Logistics Data to Improve the Delivery Experience for Consumers

#1: Most Delivery Issues in Europe Are Observed on Recipients’ End While Those in the US Are More From Carriers’ Side

Delivery problems can be caused by a variety of factors that differ from country to country. With reference to our data, most delivery issues in Europe stem from the recipients' end, whereas those in the US generally occur at the carriers' end. To be more specific, only 1.18% of US delivery issues in Q1 2022 were from the recipients’ side, possibly because it is normal for packages to be left in mailboxes or at the doorsteps across the country. Meanwhile, in Europe, 4.32% of delivery issues were from the recipients' side, with the most commonly cited reason being “(recipients) not at home”. This can perhaps be linked to the fact that several EU parcel providers, including FedEx, DHL, and Royal Mail, require a signature upon delivery by default to confirm the safe delivery of items.

Knowing the root causes of delivery failures allow retailers to manage expectations which can in turn enhance the customer experience. For instance, if issues are from the recipients’ end, retailers can consider providing more alternate delivery options such as “leave at safe place”, “leave at doorstep” etc. Meanwhile, if issues are more from the carrier’s end, businesses can use prompt delivery notifications to minimize dissatisfaction among customers.

#2: EU Customers Have Higher Demand for Same-Day Deliveries During the Weekend, Which Is Not the Case for Those in the US

Same-day (and next-day) deliveries are now a common offering in the retail industry, with many consumers expecting to receive their products in 2 hours and below. Throughout Europe last year, same-day deliveries were requested for about 9% of total deliveries each week, with the highest demand occuring on weekends - 12.8% on Saturday and 10.95% on Sunday. As most customers are not working over the weekend, they are able to stay home, receive their parcels in-person, and sign for them. This could likely be the reason why many EU customers would rather leave their shopping to the weekends and then request for same-day deliveries, considering how inconvenient it is to receive parcels on other days (especially with the requirement of a signature).

As previously said, the shipments in the US can be easily placed in the mailbox, so whether the buyers are home or not has little impact on the delivery success rate. Therefore, unlike in Europe,  US consumers did not show a particularly high demand for same-day deliveries on weekends last year. Instead, the biggest percentage of same-day shipment requests were observed on Friday for this group.

#3 The Longest Lag Time to Pick up Parcels Was Seen on Saturday in Europe and on Friday in the US

When it comes to the lag time between the checkout process of the order and parcel pick-up time, Europe and the United States saw different trends. Based on our findings, the lag time in both locations gradually increased from Monday through Saturday and then dropped on Sunday. While the greatest lag time in Europe was 2.63 days on Saturday, the US experienced the highest lag time of 2.65 days on Friday. These figures make sense as they correlate with the surge in same-day delivery requests on these specific days in the respective regions (as mentioned in the previous section).

The Duality of Big Data in Logistics

While data has the potential to boost business transformation and improve customer satisfaction, it can often get overwhelming for organizations when dealing with vast amounts of data; both structured and unstructured, and often in disparate systems. 

In the words of Karl, “the payback of doing huge data management initiatives or very long advanced analytics or machine learning initiatives may be huge, but it is very important to keep the initiatives small, iterative, and focused on unlocking value and data step by step.” He also touched on the sustainability aspect, mentioning that a business should always “have a north star plan that can be updated but towards which it is moving with every step.”

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